Research any topic before you write.

Find related topics. | Discover entities. | See connections. | Build a topical map.

Lexicographic breadth-first search

In computer science, lexicographic breadth-first search or Lex-BFS is a linear time algorithm for ordering the vertices of a graph. The algorithm is different from a breadth-first search, but it produces an ordering that is consistent with breadth-first search.

Applications, Standards & Science

Use the mouse wheel or two fingers (on touchscreens) to zoom in and out of the map.

Research this topic

Explore the main themes, entities and connections around Lexicographic breadth-first search. Start with the topic map, then use the sections below for research and deeper semantic analysis.

Explore this topic

Start with a few of the strongest sections from the source topic. These are research directions, not a list of keywords you must use.

Topics to explore

Browse the full topic structure. Each item opens a new analysis centered on that subject.

Overview

Background

Algorithm

Applications

Advanced semantic analysis

Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.

Map overview Semantic statistics

Lexicographic breadth-first search

Nodes32
Edges31
Triples28
Avg. degree1.94
Density0.0625
Components1

How this topic connects Entity context

See the strongest relationship patterns around the current topic before diving into the raw triples.

Lexicographic breadth-first search

Top relations

related to Algorithm · 10
Lexicographic breadth-first search → At, Find, For, If, In, Initialize, Move, The, Then, While
related to Chordal graphs · 7
Lexicographic breadth-first search → Continue, GFor, If, In, Let, Therefore, Use
has application · 3
Lexicographic breadth-first search → As, Bretscher, Habib
related to Graph coloring · 2
Lexicographic breadth-first search → An, For

Important terminology Word statistics

Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.

Important terminology

search graph breadth-first ordering algorithm vertices lexicographic sequence vertex set chordal output time graphs empty linear first used coloring queue

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc
breadth-first searchinstance oflike simpler graph search algorithms0.80text
depth-first searchinstance oflike simpler graph search algorithms0.80text
this algorithm takes linear time.The algorithm is called lexicographic breadth-first search because the order it produces is an ordering that could also have been produced by a breadth-first searchinstance oflike simpler graph search algorithms0.80text
and because if the ordering is used to index the rowsinstance oflike simpler graph search algorithms0.80text
columns of an adjacency matrix of a graph then the algorithm sorts the rowsinstance oflike simpler graph search algorithms0.80text
columns into lexicographical orderinstance oflike simpler graph search algorithms0.80text
Lexicographic breadth-first searchhas applicationBretscher0.60section
Lexicographic breadth-first searchhas applicationAs0.60section
Lexicographic breadth-first searchhas applicationHabib0.60section
Lexicographic breadth-first searchrelated to AlgorithmThe0.60section
Lexicographic breadth-first searchrelated to AlgorithmAt0.60section
Lexicographic breadth-first searchrelated to AlgorithmThen0.60section

Related concept clusters Concept neighborhoods

These clusters group vocabulary that occurs around closely connected concepts in the source material.

    Connections between topic areas Semantic bridges

    Bridges can reveal useful research angles that are easy to miss in a flat list of related terms.

    Min side: 3
    For writers, content strategists, SEOs, marketers and creators — from quick topic research to advanced semantic analysis.